WebFinally, our PointTAD employs an end-to-end trainable framework simply based on RGB input for easy deployment. We evaluate our proposed method on two popular benchmarks and introduce the new ... WebSpecifically, our PointTAD introduces a small set of learnable query points to represent the important frames of each action instance. This point-based representation provides a flexible mechanism to localize the discriminative frames at boundaries and as well the important frames inside the action.

Publications - GitHub Pages

Web(PointTAD) PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points (NeurIPS 2024) code (multi action detection, eg: multiTHUMOS, charades) (SoLa) Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization Tasks (arxiv 2024) WebPointTAD: Multi-Label Temporal Action Detection with Learnable Query Points @article{Tan2024PointTADMT, title={PointTAD: Multi-Label Temporal Action Detection … new kid in the neighborhood

pointtad on Twitter: "RT @83XT4HTL: โปรดมองให้เป็น ศิลปะ …

WebPointTAD: Multi-Label Temporal Action Detection with Learnable Query Points . Traditional temporal action detection (TAD) usually handles untrimmed videos with small number of action instances from a single label (e.g., ActivityNet, THUMOS). However, this setting might be unrealistic as different classes of actions often co-occur in practice. Web[NeurIPS 2024] PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points - PointTAD/main.py at main · MCG-NJU/PointTAD WebPointTAD: Multi-Label Temporal Action Detection with Learnable Query Points. no code implementations • 20 Oct 2024 • Jing Tan, Xiaotong Zhao, Xintian Shi, Bin Kang, LiMin Wang new kid in town bass cover